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affaan-m/crosspost

affaan-m

crosspost

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

global
origin:ECC
New~847
v1.3Saved Jul 14, 2026

Crosspost

Distribute content across platforms without turning it into the same fake post in four costumes.

When to Activate

  • the user wants to publish the same underlying idea across multiple platforms
  • a launch, update, release, or essay needs platform-specific versions
  • the user says "crosspost", "post this everywhere", or "adapt this for X and LinkedIn"

Core Rules

  1. Do not publish identical copy across platforms.
  2. Preserve the author's voice across platforms.
  3. Adapt for constraints, not stereotypes.
  4. One post should still be about one thing.
  5. Do not invent a CTA, question, or moral if the source did not earn one.

Workflow

Step 1: Start with the Primary Version

Pick the strongest source version first:

  • the original X post
  • the original article
  • the launch note
  • the thread
  • the memo or changelog

Use content-engine first if the source still needs voice shaping.

Step 2: Capture the Voice Fingerprint

Run brand-voice first if the source voice is not already captured in the current session.

Reuse the resulting VOICE PROFILE directly. Do not build a second ad hoc voice checklist here unless the user explicitly wants a fresh override for this campaign.

Step 3: Adapt by Platform Constraint

X

  • keep it compressed
  • lead with the sharpest claim or artifact
  • use a thread only when a single post would collapse the argument
  • avoid hashtags and generic filler

LinkedIn

  • add only the context needed for people outside the niche
  • do not turn it into a fake founder-reflection post
  • do not add a closing question just because it is LinkedIn
  • do not force a polished "professional tone" if the author is naturally sharper

Threads

  • keep it readable and direct
  • do not write fake hyper-casual creator copy
  • do not paste the LinkedIn version and shorten it

Bluesky

  • keep it concise
  • preserve the author's cadence
  • do not rely on hashtags or feed-gaming language

Posting Order

Default:

  1. post the strongest native version first
  2. adapt for the secondary platforms
  3. stagger timing only if the user wants sequencing help

Do not add cross-platform references unless useful. Most of the time, the post should stand on its own.

Banned Patterns

Delete and rewrite any of these:

  • "Excited to share"
  • "Here's what I learned"
  • "What do you think?"
  • "link in bio" unless that is literally true
  • generic "professional takeaway" paragraphs that were not in the source

Output Format

Return:

  • the primary platform version
  • adapted variants for each requested platform
  • a short note on what changed and why
  • any publishing constraint the user still needs to resolve

Quality Gate

Before delivering:

  • each version reads like the same author under different constraints
  • no platform version feels padded or sanitized
  • no copy is duplicated verbatim across platforms
  • any extra context added for LinkedIn or newsletter use is actually necessary
  • brand-voice for reusable source-derived voice capture
  • content-engine for voice capture and source shaping
  • x-api for X publishing workflows
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Overall Score

76/100

Grade

B

Good

Safety

88

Quality

72

Clarity

82

Completeness

68

Summary

A content adaptation skill that distributes user ideas across X, LinkedIn, Threads, and Bluesky while preserving author voice and respecting platform constraints. The skill guides agents through selecting a primary version, capturing voice fingerprint (via brand-voice skill), and adapting content for each platform's specific constraints and audience expectations—without producing identical cross-platform posts.

Detected Capabilities

content analysis and adaptationvoice fingerprinting and consistency checkingplatform-specific constraint applicationcross-platform publishing guidancecontent quality gatekeeping

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

crosspost contentmulti-platform distributionadapt for social platformsdistribute blog postplatform-specific postsrepost without duplicationsocial media campaignadapt voice across platforms

Risk Signals

INFO

No direct file I/O, shell execution, credential access, or network operations detected

overall skill content
INFO

Skill is instructional only—guides human/agent decision-making without triggering destructive or sensitive operations

workflow and core rules sections
INFO

References external skills (brand-voice, content-engine, x-api) but does not embed or execute them

Step 2 and Related Skills sections

Use Cases

  • Distribute a product launch announcement across four social platforms with platform-specific messaging
  • Adapt a technical blog post for both X threads and LinkedIn without duplicating content
  • Repurpose an essay or memo for multiple platforms while maintaining consistent authorial voice
  • Post a changelog or update across social media with appropriate context for each platform's audience
  • Crosspost a marketing campaign idea with platform-tailored CTAs and tone adjustments

Quality Notes

  • Strengths: Clear core rules (no identical copy, preserve voice, adapt for constraints not stereotypes) establish strong guardrails against low-quality adaptation patterns. Banned patterns section is well-defined and actionable—agents know exactly what to delete and rewrite. Workflow is logical and sequential (source → voice → platform adaptation → quality gate). Voice preservation is emphasized throughout, reducing risk of tone mismatches. Constraints are explicit (X: compressed, LinkedIn: avoid fake reflection, Threads: avoid fake casual, Bluesky: avoid feed-gaming).
  • Strengths: Posting order guidance is clear (strongest native first, stagger only if user requests). Output format is well-specified. Quality gate checklist gives agent concrete pass/fail criteria.
  • Weaknesses: No explicit guidance on how the agent should obtain or format the source content—what format should the primary version be in? (text, URL, markdown, etc.)
  • Weaknesses: 'brand-voice' and 'content-engine' skill integration is mentioned but not fully explained—agent should understand what these return and how to use their outputs. Reuse instruction ('Reuse the resulting VOICE PROFILE directly') lacks specificity on format.
  • Weaknesses: No edge case handling for very short sources (e.g., single-sentence ideas), hashtag usage across platforms (only mentioned for X/Bluesky avoidance but not for LinkedIn or Threads), or source material that is already platform-specific (e.g., a tweet being adapted to other platforms).
  • Weaknesses: 'stagger timing' mentioned for posting but not defined—what does reasonable staggering look like? No guidance on whether to post all variants or let user choose which platforms.
  • Weaknesses: No guidance on error handling—what if the primary version is too niche for LinkedIn? What if context is genuinely needed? Should agent ask user or proceed with best judgment?
Model: claude-haiku-4-5-20251001Analyzed: Jul 14, 2026

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Version History

v1.3

Content updated

2026-07-14

Latest
v1.2

Content updated

2026-04-20

v1.1

Content updated

2026-04-12

v1.0

Seeded from github.com/affaan-m/everything-claude-code

2026-03-16

Use affaan-m/crosspost in your dev environment

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